Proteomic analysis entails identification and quantitation of the proteins in complex biological mixtures. Of the present proteomic analysis methods, "shotgun" analysis, wherein the protein mixture is digested at the outset to yield an even more complex mixture of fragment peptides, is being increasingly applied. Analysis of the fragment peptides;which, like the precursor proteins, can be present in widely varying concentrations, presents a significant analytical challenge. To observe more of the peptide mixture components, particularly the fragments of low abundance proteins which are generally expected to be of greatest functional significance, requires improved methods both for separating the peptides (increasing "separation space") and for observing more of the peptides in a given separated fraction (increasing "analysis depth"). Electrospray ionization (ESI) and matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS), the primary methods used in proteomic analysis, tend to observe complementary subsets of the peptides in complex mixtures. Application of both methods gives greater coverage than either alone, but the methods entail different sample formats usually on different MS instruments and thus require more sample and more time, effort, and expense to apply both. This proposed work is directed toward increasing peptide analysis depth via use of a new platform employing nanostructured surfaces to enable application of complementary ionization modes, laser desorption ionization (LDI) and desorption electrospray ionization (DESI), to the same sample. In Aim 1, we will optimize the use of nanostructured alumina (Al2O3) surfaces for LDI and DESI analysis of peptide mixture LC separation fractions. In Aim 2, we will develop an improved DESI source to facilitate dual mode analysis of dense arrays of sample spots. The resulting platform will yield increased analysis depth as well as facilitate increasing separation space by enabling increased density of fraction collecting. The totally offline sample preparation will remove the time constraints of online analysis, which can produce inconsistency in peptide observations;improve efficiency of MS instrument time utilization;and provide an archivable medium for later reanalysis. As such, the work will significantly advance the available technologies for more complete analysis of proteomic samples. PUBLIC HEALTH RELEVANCE: Proteomics studies promise to yield new biomarkers for diagnosis and prevention of disease as well as identify new targets for development of improved therapies and disease prevention approaches. The proposed work will develop generally applicable new analytical methods that will increase the information yield from proteomics studies in wide-ranging areas of biomedical research including cardiovascular disease, cancer, and mental health to name a few.